Academic Libraries Data Analysis Using Data Mining

DOI

10.2991/nceece-15.2016.82How to use a DOI?

Keywords

Academic Libraries; Data Detection; Data Mining; Collections management; Data Analysis

Abstract

Nowadays, the requirement to preserve user privacy has avoided the preservation of data that could be used to correlate library data to non library data. This paper used data mining and data detection to identify academic library use patterns and to judge whether students' the number of published papers correlated to academic library use. All academic libraries datasets of this paper were uploaded into a data warehouse, allowing them to be managed, supervised and analyzed. The detection showed patterns of library use by academic department, patterns of book use from 2000 to 2015 15 years and statistics between the number of published papers and academic library use. The technique is demonstrated using data collected at Hohai University in China

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yuqing Shi
AU  - Yuelong Zhu
AU  - Jinghong Su
AU  - Lanfang Zhu
AU  - Dongmin Wu
AU  - Chen Lin
PY  - 2015/12
DA  - 2015/12
TI  - Academic Libraries Data Analysis Using Data Mining
BT  - Proceedings of the 2015 4th National Conference on Electrical, Electronics and Computer Engineering
PB  - Atlantis Press
SP  - 418
EP  - 421
SN  - 2352-5401
UR  - https://doi.org/10.2991/nceece-15.2016.82
DO  - 10.2991/nceece-15.2016.82
ID  - Shi2015/12
ER  -